Introduction to R Programming for Data Science
Master R programming fundamentals for data science with hands-on practice in data manipulation and analysis.
Master R programming fundamentals for data science with hands-on practice in data manipulation and analysis.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full IBM Data Analytics with Excel and R Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.5
(450 ratings)
45,785 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Learn basic R programming syntax and data types
Master common data structures like vectors, matrices, and data frames
Implement program control flow with conditions and loops
Create custom functions for data manipulation
Import and export data from various file formats
Perform web scraping and API requests
Skills you'll gain
This course includes:
1.7 Hours PreRecorded video
6 quizzes, 3 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 5 modules in this course
This comprehensive course introduces beginners to R programming for data science applications. Students learn fundamental programming concepts including data types, structures, and manipulations using RStudio and Jupyter Notebooks. The curriculum covers essential topics like vectors, matrices, data frames, control flow, functions, and working with various data formats. Through hands-on labs and practical exercises, learners develop skills in reading, writing, and analyzing data while building a strong foundation in R programming.
R Basics
Module 1 · 1 Hours to complete
Common Data Structures
Module 2 · 1 Hours to complete
R Programming Fundamentals
Module 3 · 2 Hours to complete
Working with Data
Module 4 · 1 Hours to complete
Final Project
Module 5 · 3 Hours to complete
Fee Structure
Instructor
AI and Machine Learning Expert at IBM Canada
Yan Luo serves as a Data Scientist and Developer at IBM Canada, where he applies his expertise in machine learning and artificial intelligence to develop innovative cognitive applications across diverse domains including software repository mining, personalized health management, wireless networks, and digital banking. After earning his Ph.D. in Machine Learning from the University of Western Ontario, he has contributed significantly to technical education through developing and teaching multiple data science courses, including Applied Data Science Capstone, Machine Learning Capstone, and Introduction to R Programming for Data Science. His work focuses on practical applications of AI and cognitive computing, bridging the gap between theoretical machine learning concepts and real-world business solutions.
Testimonials
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4.5 course rating
450 ratings
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.